Spectral Hashing With Semantically Consistent Graph for Image Indexing
Li, Peng1; Wang, Meng2; Cheng, Jian1; Xu, Changsheng1; Lu, Hanqing1
发表期刊IEEE TRANSACTIONS ON MULTIMEDIA
2013
卷号15期号:1页码:141-152
文章类型Article
摘要The ability of fast similarity search in a large-scale dataset is of great importance to many multimedia applications. Semantic hashing is a promising way to accelerate similarity search, which designs compact binary codes for a large number of images so that semantically similar images are mapped to close codes. Retrieving similar neighbors is then simply accomplished by retrieving images that have codes within a small Hamming distance of the code of the query. Among various hashing approaches, spectral hashing (SH) has shown promising performance by learning the binary codes with a spectral graph partitioning method. However, the Euclidean distance is usually used to construct the graph Laplacian in SH, which may not reflect the inherent distribution of the data. Therefore, in this paper, we propose a method to directly optimize the graph Laplacian. The learned graph, which can better represent similarity between samples, is then applied to SH for effective binary code learning. Meanwhile, our approach, unlike metric learning, can automatically determine the scale factor during the optimization. Extensive experiments are conducted on publicly available datasets and the comparison results demonstrate the effectiveness of our approach.
关键词Graph Laplacian Metric Learning Similarity Search Spectral Hashing
WOS标题词Science & Technology ; Technology
关键词[WOS]APPROXIMATE NEAREST-NEIGHBOR ; VIDEO ANNOTATION ; DIMENSIONALITY ; RETRIEVAL ; ALGORITHM
收录类别SCI
语种英语
WOS研究方向Computer Science ; Telecommunications
WOS类目Computer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications
WOS记录号WOS:000312646600012
引用统计
被引频次:104[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/3350
专题模式识别国家重点实验室_图像与视频分析
作者单位1.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China
2.Hefei Univ Technol, Sch Comp & Informat, Hefei 230009, Peoples R China
第一作者单位模式识别国家重点实验室
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GB/T 7714
Li, Peng,Wang, Meng,Cheng, Jian,et al. Spectral Hashing With Semantically Consistent Graph for Image Indexing[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2013,15(1):141-152.
APA Li, Peng,Wang, Meng,Cheng, Jian,Xu, Changsheng,&Lu, Hanqing.(2013).Spectral Hashing With Semantically Consistent Graph for Image Indexing.IEEE TRANSACTIONS ON MULTIMEDIA,15(1),141-152.
MLA Li, Peng,et al."Spectral Hashing With Semantically Consistent Graph for Image Indexing".IEEE TRANSACTIONS ON MULTIMEDIA 15.1(2013):141-152.
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